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Sponsored by
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ibuki95 / Affine-t2v1
Model's Last Updated: October 29 2025
text-generation
Introduction of Affine-t2v1
Model Details of Affine-t2v1
Try K2-Think · K2 Technical Report
K2-Think is a 32 billion parameter open-weights general reasoning model with strong performance in competitive mathematical problem solving.
Quickstart
Transformers
You can use
K2-Think
with Transformers. If you use
transformers.pipeline
, it will apply the chat template automatically. If you use
model.generate
directly, you need to apply the chat template mannually.
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])
Evaluation & Performance
Detailed evaluation results are reported in out Tech Report
Benchmarks (pass@1, average over 16 runs)
| Domain | Benchmark | K2-Think |
|---|---|---|
| Math | AIME 2024 | 90.83 |
| Math | AIME 2025 | 81.24 |
| Math | HMMT 2025 | 73.75 |
| Math | OMNI-Math-HARD | 60.73 |
| Code | LiveCodeBench v5 | 63.97 |
| Science | GPQA-Diamond | 71.08 |
Inference Speed
We deploy K2-THINK on Cerebras Wafer-Scale Engine (WSE) systems, leveraging the world’s largest processor and speculative decoding to achieve unprecedented inference speeds for our 32B reasoning system.
| Platform | Throughput (tokens/sec) | Example: 32k-token response (time) |
|---|---|---|
| Cerebras WSE (our deployment) | ~2,000 | ~16 s |
| Typical H100/H200 GPU setup | ~200 | ~160 s |
Safety Evaluation
Aggregated across four safety dimensions ( Safety-4 ):
| Aspect | Macro-Avg |
|---|---|
| High-Risk Content Refusal | 0.83 |
| Conversational Robustness | 0.89 |
| Cybersecurity & Data Protection | 0.56 |
| Jailbreak Resistance | 0.72 |
| Safety-4 Macro (avg) | 0.75 |
Citation
@techreport{k2think2025,
title = {K2-Think: A Parameter-Efficient Reasoning System},
author = {Zhoujun Cheng and Richard Fan and Shibo Hao and Taylor W. Killian and Haonan Li and Suqi Sun and Hector Ren and Alexander Moreno and Daqian Zhang and Tianjun Zhong and Yuxin Xiong and Yuanzhe Hu and Yutao Xie and Xudong Han and Yuqi Wang and Varad Pimpalkhute and Yonghao Zhuang and Aaryamonvikram Singh and Xuezhi Liang and Anze Xie and Jianshu She and Desai Fan and Chengqian Gao and Liqun Ma and Mikhail Yurochkin and John Maggs and Xuezhe Ma and Guowei He and Zhiting Hu and Zhengzhong Liu and Eric P. Xing},
year = {2025},
institution = {Institute of Foundation Models, Mohamed bin Zayed University of Artificial Intelligence},
url = {https://k2think-about.pages.dev/assets/tech-report/K2-Think_Tech-Report.pdf}
}
Runs of ibuki95 Affine-t2v1 on huggingface.co
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More Information About Affine-t2v1 huggingface.co Model
Url of Affine-t2v1
Affine-t2v1 huggingface.co Url
Provider of Affine-t2v1 huggingface.co
Other API from ibuki95
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